Patent application number | Description | Published |
20080301077 | System and Method for Medical Predictive Models Using Likelihood Gamble Pricing - A method for predicting survival rates of medical patients includes providing a set D of survival data for a plurality of medical patients, providing a regression model having an associated parameter vector β, providing an example x | 12-04-2008 |
20090006055 | Automated Reduction of Biomarkers - A list of biomarkers indicative of patient outcome is reduced. A computer program is applied to a set of biomarkers indicative of a patient outcome (e.g., prognosis, diagnosis, or treatment result). The computer program models the set of biomarkers with a subset of the biomarkers. The subset is identified without labeling based on the patient outcome. Instead, biomarker scores (e.g., sequence score) are used to identify the subset of biomarkers. | 01-01-2009 |
20090130096 | Gene Signature of Early Hypoxia to Predict Patient Survival - The present invention provides methods and compositions for predicting patient responses to cancer treatment using hypoxia gene signatures. These methods can comprise measuring in a biological sample from a patient the levels of gene expression of a group of the genes designated herein. The present invention also provides for microarrays that can detect expression from a group of genes. | 05-21-2009 |
20090187522 | System and Method for Privacy Preserving Predictive Models for Lung Cancer Survival Analysis - A computer-implemented method for privacy-preserving data mining to determine cancer survival rates includes providing a random matrix B agreed to by a plurality of entities, wherein each entity i possesses a data matrix A | 07-23-2009 |
20090234628 | PREDICTION OF COMPLETE RESPONSE GIVEN TREATMENT DATA - A system for modeling complete response prediction is provided. The system includes an input that is operable to receive treatment information representing treatment data that may be used to predict a complete response of a tumor. The complete response may include a disappearance of all or substantially all of a disease. A processor may be operable to use a model to predict complete response of the tumor as a function of the treatment data. The model represents a probability of complete response to treatment given the treatment data. A display is operable to output an image as a function of the complete response prediction. | 09-17-2009 |
20100057651 | Knowledge-Based Interpretable Predictive Model for Survival Analysis - Knowledge-based interpretable predictive modeling is provided. Expert knowledge is used to seed training of a model by a machine. The expert knowledge may be incorporated as diagram information, which relates known causal relationships between predictive variables. A predictive model is trained. In one embodiment, the model operates even with a missing value for one or more variables by using the relationship between variables. For application, the model outputs a prediction, such as the likelihood of survival for two years of a lung cancer patient. A graphical representation of the model is also output. The graphical representation shows the variables and relationships between variables used to determine the prediction. The graphical representation is interpretable by a physician or other to assist in understanding. | 03-04-2010 |
20110071967 | Automatic Labeler Assignment - A method, including receiving multi-labeler data that includes data points labeled by a plurality of labelers; building a model from the multi-labeler data, wherein the model includes an input variable that corresponds to the data points, a label variable that corresponds to true labels for the data points, and variables for the labels given by the labelers; and executing the model, in response to receiving new data points, to determine a level of expertise of the labelers for the new data points. | 03-24-2011 |
20110078145 | Automated Patient/Document Identification and Categorization For Medical Data - A method, including receiving a data source selection from a user or software application, the data source including medical information of a plurality of patients, receiving, from the user or software application, a data pattern that is related to a concept to be explored in the data source, querying the data source to find information that approximately matches the data pattern; and receiving the information from the data source, wherein the information includes unstructured data, assigning a classification to individual parts of the information based on the part's relationship to the data pattern, and outputting the classified information to the user or software application. | 03-31-2011 |
20110202486 | Healthcare Information Technology System for Predicting Development of Cardiovascular Conditions - Described herein is a framework for predicting development of a cardiovascular condition of interest in a patient. The framework involves determining, based on prior domain knowledge relating to the cardiovascular condition of interest, a risk score as a function of patient data. The patient data may include both genetic data and non-genetic data. In one implementation, the risk score is used to categorize the patient into at least one of multiple risk categories, the multiple risk categories being associated with different strategies to prevent the onset of the cardiovascular condition. The results generated by the framework may be presented to a physician to facilitate interpretation, risk assessment and/or clinical decision support. | 08-18-2011 |
20140088989 | Rapid Learning Community for Predictive Models of Medical Knowledge - A predictive model of medical knowledge is trained from patient data of multiple different medical centers. The predictive model is machine learnt from routine patient data from multiple medical centers. Distributed learning avoids transfer of the patient data from any of the medical centers. Each medical center trains the predictive model from the local patient data. The learned statistics, and not patient data, are transmitted to a central server. The central server reconciles the statistics and proposes new statistics to each of the local medical centers. In an iterative approach, the predictive model is developed without transfer of patient data but with statistics responsive to patient data available from multiple medical centers. To assure comfort with the process, the transmitted statistics may be in a human readable format. | 03-27-2014 |
20140095201 | Leveraging Public Health Data for Prediction and Prevention of Adverse Events - An adverse event may be prevented by predicting the probability of a given patient to have or undergo the adverse event. The ability to predict the probability of the adverse event may be enhanced when a model is derived from public health data to categorize and propose values for medical record fields. The probability alone may prevent the adverse event by educating the patient or medical professional. The probability may be predicted at any time, such as upon entry of information for the patient, periodic analysis, or at the time of admission. The probability may be used to generate a workflow action item to reduce the probability, to warn, to output appropriate instructions, and/or assist in avoiding adverse event. The probability may be specific to a hospital, physician group, or other medical entity, allowing prevention to focus on past adverse event causes for the given entity. | 04-03-2014 |
20140095203 | MEDICAL WORKFLOW DETERMINATION AND OPTIMIZATION - Workflows for medical entities are determined and evaluated by determining a plurality of medical tasks based on an analysis of a plurality of electronic medical records of a medical entity. A workflow of the medical entity is determined based on a sequence of medical tasks, the sequence determined based on the analysis of the plurality of electronic medical records, and an evaluation of the workflow is performed based on a predefined criterion. | 04-03-2014 |
20140095204 | AUTOMATED MEDICAL COHORT DETERMINATION - Inclusion of a patient in a medical category is determined by triggering an analysis of an electronic medical record of the patient in response to an input of data into the electronic medical record. Identifying characteristics that indicate inclusion in the medical category with the analysis, and determining a probability the patient belongs to the medical category based on the identified characteristics. | 04-03-2014 |
20140095205 | AUTOMATED MAPPING OF SERVICE CODES IN HEALTHCARE SYSTEMS - Automatic mapping of semantics in healthcare is provided. Data sets have different semantics (e.g., Gender designated with M and F in one system and Sex designated with 1 or 2 in another system). For semantic interoperability, the semantic links between the semantic systems of different healthcare entities are created (e.g., Gender=Sex and/or 1=F and 2=M) by a processor from statistics of the data itself. The distribution of variables, values, or variables and values, with or without other information and/or logic, is used to create a map from one semantic system to another. Similar distributions of other variable and/or values are likely to be for variables and/or values with the same meaning. | 04-03-2014 |
20140095206 | ADAPTIVE MEDICAL DOCUMENTATION SYSTEM - Adaptive medical data collection for medical entities may involve triggering an analysis of electronic records in response to information input into an Electronic Medical Record (EMR) of a patient. Determining a potential condition for the patient based on the analysis. Identifying additional information indicated as relevant to the potential condition of the patient, and generating a request for the identified additional information. | 04-03-2014 |
20140214451 | Adaptive Medical Documentation System - Adaptive medical data collection for medical entities may involve managing content by receiving data indicating a context, identifying at least one application or knowledge base associated with the context, designating the identified application or knowledge base as active, and accessing the active application or knowledge base to provide information at an interface point for a medical professionals and a patient. | 07-31-2014 |